Prior Cosmetic Techniques and Their Disadvantages
Prior art techniques for modifying the appearance of skin include natural tanning, artificial tanning, and the deliberate application of cosmetics. Each of these prior art techniques has limitations.
Typically, the applications of cosmetic substances to skin are largely manual, for example through the use of brushes, application tubes, pencils, pads, and fingers. The application methods make prior art cosmetics imprecise, labor intensive, expensive, and sometimes harmful, when compared to the computerized techniques of the present invention.
Most prior art cosmetic approaches are based on the application of opaque substances. There is a need for the precise application of reflectance modifying agents (RMAs), such as transparent dyes, to provide a more effective modification of appearance.
Manual cosmetic applications are imprecise compared to computer-controlled techniques, and this imprecision may make them less effective. For example, the heavy application of a foundation base for makeup may cause an unattractive, caked-on appearance. Manual techniques also typically take a long time to employ, as can be seen in any morning commute on a highway, where people frantically take advantage of stops to finish applying their makeup. In addition, manually applied makeup is not cheap, and when the help of professionals such as beauticians is required, is even more expensive. Moreover, often the materials applied to the skin in manual techniques are themselves potentially harmful. For example, a foundation base for makeup may cause skin to dry out and may inhibit the skin's breathing. Sunlight or artificial light used for tanning may cause cancer.
Therefore, there is a need for the precise application of reflectance modifying agents (RMAs) to provide a more effective, more automated, faster, less expensive, and less dangerous modification of the appearance of skin. The cross-referenced U.S. patent application cited above presents a system and method for this need.
In this specification, the terms “reflectance modifying agent” or “RMA” refer to any compound useful for altering the reflectance of another material. Some examples of RMA are inks, dyes, pigments, bleaching agents, chemically altering agents, and other substances that can alter the reflectance of human skin and other features. The terms “dye” and “transparent dyes” are used for brevity in this specification to represent any RMA.
Consumers of cosmetics also need effective techniques that allow them to select desired cosmetic enhancements, such as different shades of makeup, to visualize how those enhancements will look on them, for example on computer displays, and to precisely apply cosmetics onto them to make the selected enhancements. Websites such as MaryKay.com offer virtual makeovers that allow users to try out on their home computer displays different makeup patterns on digital images of different types of women and even on digital images of the users themselves that users submit. However, the images used in virtual makeovers do not provide adequate details for the calculation of advanced RMA enhancements. Nor do they allow users to automatically apply to themselves the cosmetic enhancements that have selected digitally on computer displays. There is a need for a method that lets users employ an RMA applicator and a computer display to view sufficiently detailed digital images of themselves so that they can make virtual cosmetic enhancements to those images and so that they can automatically and precisely apply RMA to themselves to achieve those enhancements.
Consumers also need effective techniques that allow them to make cosmetic enhancements not just to a single area, such as a facial blemish, but over their whole bodies. For example, some people get natural or artificial tans to make their skin look smoother and thus more attractive over their whole bodies. Consumers in East Asia often use cosmetics to make much of their skin look lighter. Consumers also may want to make complex cosmetic enhancements, involving color and texture, to hide defects and enhance their appearance over their whole bodies. Manual techniques to make such whole body cosmetic enhancements can be particularly laborious, time-consuming, and expensive. There is a need for a system and method that lets users make automatic cosmetic enhancements to their whole bodies.
Simulated Digital Images
In this patent application, a “simulated image” refers to a digital image that simulates a real object and can be displayed on a computerized device. A simulation of a real object is a portrayal of the object in any desired manner not strictly limited to aspects revealed by photographic or video data captured about the object. A simulated image can represent a still image of the object or a video clip of the object in motion and may be three dimensional (3D). For example, simulated images are widely used for display on computer screens, cell phones, video games, in animated sections of movies, and in medical imaging.
In general, consumers want to display very realistic simulated images in different media. Moreover, they may want simulated images that represent subjects that they choose. For example, these subjects may be the consumers themselves, their friends, their family members, or their favorite personalities such as movie stars. For instance, a boy may want to put his own face on a 3D action figure in a video game. A woman may want to display a simulated 3D image of her face and head on a computer device and make cosmetic enhancements to that image, so that she can try out different cosmetic effects and hairstyles virtually.
In addition, consumers may want simulated images that are enhanced to be more desirable in some way. For example, a person may want his or her own face to be displayed in a way that makes him or her appear younger and more attractive.
Prior Techniques and Their Disadvantages
Simulated images have been created in a number of ways. They can be drawn by hand and then scanned, photographed, or video recorded and can be created through computer graphics programs, both of which are laborious techniques requiring special skills.
In addition, simulated images can be created by using sensors attached at various points to a real subject, digitally recording the motions the subject, often through multiple cameras, and using computer graphics programs to create simulated characters whose movements and facial expressions are based on those of the recorded subject. In this way, an animation of a cartoon character dancing or smiling may be based on a real actor's movements and expression.
The computer graphics programs used in these processes are increasingly able to transform recorded data about real objects into simulated images. An example is Optasia™, the model-based feature-recognition platform developed by Image Metrics, PLC. The “Technical White Paper” on the Image Metrics Website states that “The Optasia engine can perform rapid model-to-image matching regardless of the model type, including those with high-frequency elements such as texture.” Optasia is available on a variety of platforms as a three-layered architecture. All systems use 1) the Optasia core, with 2) a sector specific API (e.g. medical image analysis). Prior knowledge is incorporated in the 3) ‘expert’ layer (or model).
However, such prior techniques have disadvantages:                They are all labor intensive and require special skills and special, often cumbersome equipment not readily available to many consumers.        The simulated images they produce have limited details so that they do not look as realistic as consumers want. Instead, they tend to look artificially smoothed, often because their computer graphics programs must fill in large areas of simulated images with what essentially amounts to guesses and averages as a result of limited collection of data about the subject. These guesses and averages may require complicated algorithms and large amounts of computing power. For example, the three-layered approach of Optasia, mentioned above, is complicated and computing intensive.        They are difficult for consumers themselves to use to simulate favorite images.        They are difficult for consumers to use to enhance simulated images in desirable ways.        Moreover, they are not readily available to many consumers, who may not have access to expensive modeling and graphics software and equipment.        
Therefore, there is a need for an automated cosmetic monitoring and enhancement system that can be readily available to consumers, is easy to use, and provides high-resolution realistic image files with rich data about real subjects that can be used for creating simulated images.